Lecture19_Chapter4

Lecture19_Chapter4 - Lecture 19 Chapter 4 Wednesday,...

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Lecture 19 – Chapter 4 Wednesday, October 29 th
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Normal distribution ± “Normal distribution is a statistical unicorn” ± It is the most important distribution in statistics. ± Most of the random variables out in nature fit naturally to normal distribution ± Of course, it is a distribution for continuous random variables
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Normal distribution ± A continuous random variable is said to have a normal distribution with parameters and if the pdf of X is: ± We denote this as μ 2 σ () 2 2 2 2 2 1 ;, , 2 x fx e x μσ πσ = −∞< <∞ ( ) 2 ~, XN
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Standard Normal curve ± The standard normal curve is the normal curve that has and . ± The standard normal random variable is denoted by Z. ± The pdf of Z is: ± The cdf of Z is denoted with 0 μ= 2 1 σ = () 2 2 1 ;0,1 2 z f ze π = ( ) ( ) z PZ z Φ =≤
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Using the Tables ± One can use the Table A.3 in Appendix A to find the cumulative density distribution of standard normal curve.
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This note was uploaded on 09/23/2009 for the course STAT 318 taught by Professor Staff during the Fall '08 term at Penn State.

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Lecture19_Chapter4 - Lecture 19 Chapter 4 Wednesday,...

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